A logistic regression function (CIPI) has been developed and statistically validated which predicts the probability of acute ischemic heart disease (AIHD) in patients presenting to the Emergency Room (ER). CIPI was based on retrospective analysis of 174 clinical, electrocardiographic, historical, risk factor, socioeconomic, and organizational variables. The study sample consisted of 854 patients presenting to the Boston City Hospital Emergency Room with symptoms suggestive, but not diagnostic, of AIHD. CIPI is comprised of nine variables, including ECG changes and patient reports of symptoms and past medical history. Its diagnostic capability is similar to the ER physicians, correctly classifying 85% of all cases as AIHD or non-AIHD patients. The use of CIPI as a supplementry diagnostic tool is currently being tested at Boston City Hospital in a prospective randomized trial. In alternate months, ER physicians are informed of the CIPI probability in each patient presenting with possible AIHD symptoms. Results on the first 330 patients indicate that the availability of CIPI in the ER significantly improves diagnostic accuracy. During experimental months, correct classification of patients as AIHD or non-AIHD rose 12% over those months when physicians did not receive CIPI. More importantly, the false positive CCU admission rate fell from 57% to 34%, while the false negative discharges remained at their acceptably low level.